1 Palmer Penguins

This example uses the Palmer Penguins data set: https://github.com/allisonhorst/palmerpenguins.

Palmer Penguins Illustration from @allison_horst

Illustration of Culmen

2 Get Data

library(palmerpenguins)

data("penguins")

3 Replay The Data Set (May Not Look So Great)

penguins
## # A tibble: 344 x 7
##    species island culmen_length_mm culmen_depth_mm flipper_length_… body_mass_g
##    <fct>   <fct>             <dbl>           <dbl>            <int>       <int>
##  1 Adelie  Torge…             39.1            18.7              181        3750
##  2 Adelie  Torge…             39.5            17.4              186        3800
##  3 Adelie  Torge…             40.3            18                195        3250
##  4 Adelie  Torge…             NA              NA                 NA          NA
##  5 Adelie  Torge…             36.7            19.3              193        3450
##  6 Adelie  Torge…             39.3            20.6              190        3650
##  7 Adelie  Torge…             38.9            17.8              181        3625
##  8 Adelie  Torge…             39.2            19.6              195        4675
##  9 Adelie  Torge…             34.1            18.1              193        3475
## 10 Adelie  Torge…             42              20.2              190        4250
## # … with 334 more rows, and 1 more variable: sex <fct>

4 Descriptive Statistics

# summary(penguins)

# psych gives a good list of descriptive statistics

psych::describe(penguins) 
##                   vars   n    mean     sd  median trimmed    mad    min    max
## species*             1 344    1.92   0.89    2.00    1.90   1.48    1.0    3.0
## island*              2 344    1.66   0.73    2.00    1.58   1.48    1.0    3.0
## culmen_length_mm     3 342   43.92   5.46   44.45   43.91   7.04   32.1   59.6
## culmen_depth_mm      4 342   17.15   1.97   17.30   17.17   2.22   13.1   21.5
## flipper_length_mm    5 342  200.92  14.06  197.00  200.34  16.31  172.0  231.0
## body_mass_g          6 342 4201.75 801.95 4050.00 4154.01 889.56 2700.0 6300.0
## sex*                 7 333    1.50   0.50    2.00    1.51   0.00    1.0    2.0
##                    range  skew kurtosis    se
## species*             2.0  0.16    -1.73  0.05
## island*              2.0  0.61    -0.91  0.04
## culmen_length_mm    27.5  0.05    -0.89  0.30
## culmen_depth_mm      8.4 -0.14    -0.92  0.11
## flipper_length_mm   59.0  0.34    -1.00  0.76
## body_mass_g       3600.0  0.47    -0.74 43.36
## sex*                 1.0 -0.02    -2.01  0.03

5 Use Pander To Format Our Summary Results

library(pander)

pander(psych::describe(penguins))
Table continues below
  vars n mean sd median trimmed mad
species* 1 344 1.919 0.8933 2 1.899 1.483
island* 2 344 1.663 0.7262 2 1.58 1.483
culmen_length_mm 3 342 43.92 5.46 44.45 43.91 7.042
culmen_depth_mm 4 342 17.15 1.975 17.3 17.17 2.224
flipper_length_mm 5 342 200.9 14.06 197 200.3 16.31
body_mass_g 6 342 4202 802 4050 4154 889.6
sex* 7 333 1.505 0.5007 2 1.506 0
  min max range skew kurtosis se
species* 1 3 2 0.1591 -1.732 0.04816
island* 1 3 2 0.6086 -0.9064 0.03915
culmen_length_mm 32.1 59.6 27.5 0.05265 -0.8931 0.2952
culmen_depth_mm 13.1 21.5 8.4 -0.1422 -0.9234 0.1068
flipper_length_mm 172 231 59 0.3427 -0.9992 0.7604
body_mass_g 2700 6300 3600 0.4662 -0.7395 43.36
sex* 1 2 1 -0.01794 -2.006 0.02744

6 Only Look At A Subset of Variables

mynewdata <- subset(penguins, select = c(species,
                                         island,
                                         body_mass_g))

pander(psych::describe(mynewdata))
Table continues below
  vars n mean sd median trimmed mad
species* 1 344 1.919 0.8933 2 1.899 1.483
island* 2 344 1.663 0.7262 2 1.58 1.483
body_mass_g 3 342 4202 802 4050 4154 889.6
  min max range skew kurtosis se
species* 1 3 2 0.1591 -1.732 0.04816
island* 1 3 2 0.6086 -0.9064 0.03915
body_mass_g 2700 6300 3600 0.4662 -0.7395 43.36

7 “Hand Built” Table

Things Outcome
Thing 1 A
Thing 2 B